Players’ performance during worst-case scenarios in professional soccer matches: a systematic review

Since the analysis of worst-case scenarios (WCS) has been increasing knowledge about match demands and possible impacts for the training process, it seems important to summarize the evidence to provide useful information for the soccer community. Thus, the purpose of this systematic review was to summarize the evidence about WCS in professional soccer. A systematic review of PubMed, SPORTDiscus, and FECYT (Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO) was performed according to the guidelines for performing systematic reviews in sport science. From the 85 studies initially identified, 12 were fully reviewed, and their outcome measures were extracted and analyzed. There was an inverse relationship between the duration of WCS windows and running output during match play. Occurrences of WCS during soccer matches were also position-dependent across studies, at least, when analyzing performance with the total distance covered variable, although different outputs were identified between women and men players. Future research should consider analyzing the impact of contextual variables (match status, team formation, and match location) on peak match values and the weight of these moderators.


INTRODUCTION
Match running performance in soccer is a well-researched topic in match analysis [1]. Using different tracking approaches, the collection and description of distances covered at different speed thresholds, accelerations, decelerations, or mechanical load parameters have been described considering different situational factors [2], sexes [3,4], or other variables. The understanding of the typical values of activity profiles provided a better understanding of the volume of running and identification of the weight of each type of running intensity in the volume of running and the consequences for training [5].
Despite the importance of describing the volume of running performed, the relativization of game pace and value (activity profile per minute) is important to consider the players who have not participated in the whole match [6]. Additionally, the relative meters or number of actions performed per minute can also help to identify the typical pace for adjusting some training drills based on running [7].
The screening of the title, abstract and reference list of each study to locate potentially relevant studies was independently performed by the two authors. Additionally, they reviewed the full version of the included papers in detail to identify articles that met the selection criteria. An additional search within the reference lists of the included records was conducted to retrieve additional relevant studies.
Possible errata for the included articles were considered.
The inclusion and exclusion criteria can be found in table 1.

Data Extraction
The following information was extracted from the included original articles: EPTS, level (league) and players´ mean age, sample, playing positions, variable and time epoch.

Methodological Assessment
Methodological assessment process was performed by two authors (MRG and JPO) using an adapted version of the STROBE assessment criteria for cross-sectional studies [20], looking studies eligible for inclusion. Each article was assessed based on 10 specific criteria (Table 2). Any disagreement was discussed and solved by consensus decision. Each item was evaluated using numerical characterization (1 = completed; and, 2 = non-completed), where a study with 7 points scored was qualified as a low quality (high risk of bias) and a study with 8 points scored was qualified as a study with low risk of bias [20].

Study identification and selection
The searching of databases identified a total of 85 titles. These studies were then exported to reference manager software. Duplicates (43 references) were subsequently removed manually. The remaining 42 articles were screened for their relevance based on titles and abstracts, resulting in the removal of a further 30 studies. Following the screening procedure, 12 articles were selected for in depth reading and analysis. After reading full texts, all of these studies were included in the qualitative synthesis ( Figure 1).

Methodological quality
The overall methodological quality of the studies can be found in Table 2.

Characteristics of individual studies
The characteristics of the included studies are shown in Table 3 (male players: n = 10 studies) and 4 (female players: n = 2 studies). All studies were developed with professional athletes. Playing position data were included in both tables 3 and 4 with exception for one study [26]. There was one study that data was non-extractable [27].
Both tables 3 and 4 included data by epochs (from 1 min to 10 min) for all variables analysed by each study, respectively. Naturally, the peak match running demands in shorter epochs are much more intense than in longer epochs independently of sex [13,14]. Similarly to considering the whole match, the WCS seem also to be dependent on situational factors [10,15]. Among these, average match demands for the whole match or WCS are highly position-dependent, thus playing positions should be considered since the values significantly differ from position to position [10].
This should be carefully considered for recovery strategies, training interventions and individualization of the training process [16].
Since the analysis of WCS has been increasing knowledge about match load demands and possible impacts for the training process, it seems important to summarize the evidence to provide useful information for the sports community. Despite the publication of a systematic review about the use of microtechnology to quantify the peak match demands in football codes [17], a systematic review is still needed that allows the comparison of peak match demands among time windows, playing positions, sexes and contextual factors in professional soccer. This information will help towards an understanding of the current state-of-the-art and indicate new routes for research into WCS in soccer. Therefore, the purpose of this systematic review was to summarize the evidence about WCS in professional soccer.

MATERIALS AND METHODS
The systematic review strategy was conducted according to the guideline for performing systematic reviews in sport science [18].

Search strategy
PubMed, SPORTDiscus, and FECYT, which contains seven databases (i.e. Web of Sciences, CCC, DIIDW, KJD, MEDLINE, RSCI, and SCIELO), were searched for relevant publications prior to March 22, 2021. Keywords and synonyms were entered in various combinations in the title, abstract or keywords: (soccer OR football) AND ("worst case scenario*" OR "most demanding passage*"). Additionally, the reference lists of the studies retrieved were manually searched to identify potentially eligible studies not captured by the electronic searches. Finally, an external expert has been contacted in order to verify the final list of references included in this scoping review in order to understand if there was any study that was not detected through our research. Possible errata were searched for each included study.

Study selection
A data was prepared in Microsoft Excel sheet (Microsoft Corporation, Readmon, WA, USA) in accordance with the Cochrane Consumers and Communication Review Group's data extraction template [19].
The Excel sheet was used to assess inclusion requirements and subsequently tested for all selected studies. The process was independently conducted by the two authors (MRG and JPO). Any disagreement regarding study eligibility was resolved in a discussion.

Intervention
The data were recorded during soccer matches.
The data were recorded during training sessions.

Outcome
Physical/physiological, technical and/or tactical performance outcomes.

Study Design
Soccer players performance during the most demanding passages. -

Additional criteria Only original and full-text studies written in English
Written in other language than English. Other article types than original (e.g., reviews, conference abstracts, etc.). Note: provide in the abstract an informative and balanced summary of what was done and what was found (item 1); state specific objectives, including any prespecified hypotheses (item 2); Give the eligibility criteria, and the sources and methods of selection of participants (item 3); for each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group (item 4); explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why (item 5); give characteristics of study participants (item 6); summarize key results with reference to study objectives (item 7); discuss limitations of the study, considering sources of potential bias or imprecision. Discuss both direction and magnitude of any potential bias (item 8); give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar studies, and other relevant evidence (item 9); give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the present article is based (item 10). The most demanding passages in soccer       The most demanding passages in soccer defending team can stop the progression of the attacking team towards its goal, the steady state will be regained, while if the defending team cannot, a chaotic situation will arise [31], leading to WCS. In soccer literature, it has been highlighted that the relationship between play-ers´ physical fitness and ranking outcomes is poor [32,33], emphasizing teams´ technical and tactical effectiveness rather than high levels of physical performance [33]. However, further studies could consider if the player´s physical condition may be more relevant in WCS. To date, the WCS have been analyzed using some factors that have influenced the extracted outcomes. Therefore, to analyze the influence of each of them may be of interest for soccer community.

Worst-case scenarios depending on the time window
Since high-intensity actions have been included in the principal components that explained players´ performance [34,35], interest in analyzing WCS has grown exponentially. Since different authors have found the influence of different epochs in running outputs (     should be considered to understand WCS in soccer. In soccer, two teams face one another with exactly opposite aims, leading players to organize themselves with teammates and consider the opponents´ behavior. In this scenario, a player´s movement (teammate or opponent) induces another player´s adaptation, which subsequently provokes the adaptation of another. In this respect, soccer has been highlighted as a game involving continuous adaptations and re-adaptations [29]. Considering this concept, the team with possession shares the ball through passes between teammates, who move along the field providing solutions for the player with the ball [30]. This collective behavior of the attacking team is counteracted by individual defending player behavior, combining into collective defending behavior, confronting each other opposite strategies.
In this scenario, while team-to-team, or specifically, player-to-player synchronization remains, a steady state dominates [31]. However, when one of the attacking player's movements (usually high-intensity movement) breaks player-to-player synchronization, the remaining players leave their position to alleviate the defensive imbalance, trying to recover the general equilibrium [31]. Therefore, if the following one, in this case 2-min. For example, the analysis reported  [38,39], it was expected that players´ performance may differ during WCS.
In soccer literature, it has been highlighted that MD traveled the longest average distance during competition, followed by F and defenders [33,40,41]. Regarding HSR, full-backs, MD, and advanced MD covered a greater distance, while CD and F covered more distance at high power [42]. In brief, players´ performance is dependent on their playing positions, at least, since WD, WM, and M perform more m/min than the others. However, differences among playing positions do not seem large in those variables that explain players´ performance at highintensity. Accordingly to most studies (~85%; 11/13 studies) [14,15,17,23,24,[26][27][28][29][30], it is recommended that results provided during WCS serve as the basis for future training prescription, in order to respect the specific demands imposed on players during the most demanding passages of match play. However, despite these common results between sexes, the differences between them seems to be a fact. Although women soccer players have shown greater values in some variables such as core endurance [44], the largest sex differences were evident in the explosive and intermittent endurance-related variables, with women

Worst-case scenarios depending on sex
showing lower values (large to extreme) in sprints, jumps, and intermittent endurance, and trivial to moderate differences (lower in women) in running velocity, maximal heart rate, and distance covered during incremental exercises [44]. These results lead to the hypothesis that sex differences will remain in WCS during soccer matches.
In this systematic review, there were differences between men and women in distance covered (115-233 and 110-157 m/min), HSR The most demanding passages in soccer making systematic recommendations unfeasible to date. (6) To end, the generalizability of current evidence to assist periodization in training is debatable [10,28,36]. Limitations derived either from methods adopted here or from articles considered should be carefully taken into account when interpreting systematic conclusions made, and future research is advisable to follow up such concerns. Future research should consider understanding the better methodology for measuring WCS aiming to reduce the noise, as well as determine the practical implications for real-training scenarios as to how to prescribe based on typical values.

Funding
No other specific sources of funding were used to assist in the preparation of this article.

Conflicts of interest/Competing interests
The authors declare that they have no conflicts of interest relevant to the content of this systematic review. in the number of accelerations (2-4 and 0,6-0,9 n/min), respectively. These differences may arise due to anthropometric and physiological differences between the genders [45].

Worst-case scenarios depending on contextual factors
Three studies assessed the impact of a range of contextual variables regarding the expression of WCS over match-play [12,15,46]. For short passages (1-to 3-min), match outcome was a significant independent factor since winners reported a higher running performance [10,12]. Nevertheless, considering longer periods the literature showed opposed conclusions supporting [12] or contesting this result [10]. Match location impacted WCS observed in [10] whilst the study by Fereday and co-workers [12] indicated no effects in either total or high-speed distances. Finally, playing formation also contributed to WCS variations in two investigations [12,15]. As a consequence, this indicates that previous literature on match performance in soccer [47][48][49] cannot be always extrapolated when analyzing the WCS in this team sport, implying a need to control for contextual constraints even in the absence of a clear consensus in some cases. In this regard, replication studies in distinct populations/locations, standards, and ages are still required to provide strong evidence, which is currently scarce according to our searches.

Study limitations
Six main issues are recognized in the present review study: (1) Aside from the acceptable methodological scores of the majority of the papers included, there were some (14%) that did not reach highquality levels.
(2) Except in one study separating offensive and defensive game phases using a semi-automatic video tracking method [16] and another considering ball in/out of play by custom-built software coding [32], the results collected here may also lack the context in which they occurred (see for more information: [47]). This is due to the predominant use of only portable micro technologies to collect match performance (~86%) [13,14,17,[23][24][25][26][27][28][29][30][31], which alone may not allow capturing technical event occurrences like losing and regaining ball possession [48]. (3) Most importantly, whether there was any variation in players' actual positions occupied during matches in relation to intended formation was not reported in all except two studies [27,28], thereby indicating a need to re-examine some of the methods. One potential solution is to apply heat maps to the 2-dimensional positional data to confirm if each player indeed exerted a role predominantly in a given field location [50] (4) The information gathered is pertinent to a greater extent to men professional players, because only two literature studies determined in-game WCS in professional women [25,28] soccer athletes. (5) Some pertinent topics consisted only of isolated/single studies (e.g. congested schedule [51], player status (such as starter/non-starter comparisons) [12], and match-to-match variability [28]), thereby